Com o teste de Moran verificamos se existe efeito/correlação espacial. Estatísticas maiores que o valor esperado indicam correlação espacial positiva. Valores menores indicam correlação negativa.
Em vermelho, tudo que for significativo no nível de 5%.
| var | Moran I statistic | Expectation | Variance | p-value |
|---|---|---|---|---|
| Mediana | 0.5152366 | -0.00017963 | 6.63265e-05 | 0 |
| Média | 0.7432000 | -0.00017963 | 6.65052e-05 | 0 |
| PCA | 0.7612687 | -0.00017963 | 6.65123e-05 | 0 |
| Moran I statistic | Expectation | Variance | p-value |
|---|---|---|---|
| 0.433899 | -0.00017963 | 6.65876e-05 | 0 |
| var | Moran I statistic | Expectation | Variance | p-value |
|---|---|---|---|---|
| Mediana | 0.6240121 | -0.00017963 | 6.64841e-05 | 0 |
| Média | 0.6240121 | -0.00017963 | 6.64841e-05 | 0 |
| PCA | 0.5046265 | -0.00017963 | 6.65366e-05 | 0 |
| var | Moran I statistic | Expectation | Variance | p-value |
|---|---|---|---|---|
| Mediana | 0.6690636 | -0.00017963 | 6.56291e-05 | 0 |
| Média | 0.6690636 | -0.00017963 | 6.56291e-05 | 0 |
| PCA | 0.6785039 | -0.00017963 | 6.57205e-05 | 0 |
| var | Moran I statistic | Expectation | Variance | p-value |
|---|---|---|---|---|
| Mediana | 0.5268894 | -0.00017963 | 6.63615e-05 | 0 |
| Média | 0.5268894 | -0.00017963 | 6.63615e-05 | 0 |
| PCA | 0.3504746 | -0.00017963 | 6.63125e-05 | 0 |
| Moran I statistic | Expectation | Variance | p-value |
|---|---|---|---|
| 0.9308503 | -0.00017963 | 6.65538e-05 | 0 |
A análise estatística foi realizada no ambiente de computação estatística
R(R Core Team, 2022). Os principais pacotesRutilizados foram o {dplyr} (Wickham et al., 2022), {tidyr} (Wickham & Girlich, 2022), {rlang} (Henry & Wickham, 2022), {purrr} (Henry & Wickham, 2020), {ggplot2} (Wickham, 2016), {patckwork} (Pedersen, 2020), {geobr} (Pereira & Gonçalves, 2022), e {spdep} (Bivand, 2022; Bivand et al., 2013).
R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
Wickham, H., François, R., Henry, L., Müller, K. (2022). dplyr: A Grammar of Data Manipulation. R package version 1.0.9. https://CRAN.R-project.org/package=dplyr
Wickham, H., Girlich, M. (2022). tidyr: Tidy Messy Data. R package version 1.2.0, https://CRAN.R-project.org/package=tidyr
Henry, L., Wickham, H. (2022). rlang: Functions for Base Types and Core R and ‘Tidyverse’ Features. R package version 1.0.2, https://CRAN.R-project.org/package=rlang
Henry, L., Wickham, H. (2020). purrr: Functional Programming Tools. R package version 0.3.4, https://CRAN.R-project.org/package=purrr
Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York
Pedersen, T. L. (2020). patchwork: The Composer of Plots. R package version 1.1.1. https://CRAN.R-project.org/package=patchwork
Pereira, R. H. M., Gonçalves, C. N. (2022). geobr: Download Official Spatial Data Sets of Brazil. R package version 1.6.5999, <https://github.com/ipeaGIT/geobr
Bivand, R. S. (2022) R Packages for Analyzing Spatial Data: A Comparative Case Study with Areal Data Geographical Analysis URL https://doi.org/10.1111/gean.12319
Bivand, R. S., Pebesma, E., Gomez-Rubio, V. (2013). Applied spatial data analysis with R, Second edition. Springer, NY. https://asdar-book.org/